3) Global localization retrieves the global pose of mobile agents in a known scene with prior knowledge. This is achieved by matching the inquiry input data with a pre-built 2D or 3D map, other spatial references, or a scene that has been visited before.
It can be leveraged to reduce the pose drift of a dead reckoning system or solve the 'kidnapped robot' problem[1]}.
Deep learning is used to tackle the tricky data association problem that is complicated by the changes in views, illumination, weather and scene dynamics, between the inquiry data and map.
